----------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/singh/Google Drive/PLS/Research/Compulsory Voting/ERG CV/R&P submission materials/replication log,
>  R&P.log
  log type:  text
 opened on:  29 Aug 2017, 18:45:47

. use "/Users/singh/Google Drive/PLS/Research/Compulsory Voting/ERG CV/R&P submission materials/replication data, R&P.
> dta", clear

. do "/var/folders/63/8fq62ffn6sng8s9wbw2p6m74rd1twr/T//SD11996.000000"

. 
. 
. ********
. *Define sample
. ********
. reg polit_soph b1.voteprob_if_no_fine_AU time_on_camp_min totallinks polls_treatment 

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  6,  1910) =   72.21
       Model |  242.049955     6  40.3416592           Prob > F      =  0.0000
    Residual |  1067.00938  1910  .558643655           R-squared     =  0.1849
-------------+------------------------------           Adj R-squared =  0.1823
       Total |  1309.05934  1916  .683225124           Root MSE      =  .74742

----------------------------------------------------------------------------------------------
                  polit_soph |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.4310476   .0388529   -11.09   0.000    -.5072462    -.354849
Moderately Compelled Voters  |   -.864542   .0566402   -15.26   0.000    -.9756251   -.7534589
  Strongly Compelled Voters  |  -1.096897   .0844761   -12.98   0.000    -1.262572    -.931222
                             |
            time_on_camp_min |  -.0227796   .0102184    -2.23   0.026      -.04282   -.0027392
                  totallinks |   .0196158   .0043948     4.46   0.000     .0109968    .0282349
             polls_treatment |   .0101061   .0364777     0.28   0.782    -.0614343    .0816464
                       _cons |   .2877465   .0363179     7.92   0.000     .2165197    .3589733
----------------------------------------------------------------------------------------------

. gen samp = 1 if e(sample)
(303 missing values generated)

. 
. ********
. *Set Version
. ********
. version 13.1

. 
. 
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. *FIGURE 2
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. *first, generate variables to use in area plots
. kdensity time_on_camp_min if samp == 1, bw(.6) gen(x_values_time_on_camp_min density_values_time_on_camp_min)

. kdensity totallinks if samp == 1, bw(1.3) gen(x_values_totallinks density_values_totallinks)

. 
. *then make density plots
. twoway ///
>         (area density_values_time_on_camp_min x_values_time_on_camp_min if samp == 1, fcolor(gs7*.9)  fintensity(100
> ) lcolor(gs7*.9) lwidth(medthick)) ///
>         , scheme(s1mono)  ///
>         xtitle("Number of Minutes Spent Gathering Information") ///
>         ytitle("Density") ylabel(0(.1).4) yscale(range(0 .4)) ///
>         name(time_on_camp_min_density, replace)

.         
. twoway ///
>         (area density_values_totallinks x_values_totallinks if samp == 1, fcolor(gs7*.9)  fintensity(100) lcolor(gs7
> *.9) lwidth(medthick)) ///
>         , scheme(s1mono)  ///
>         xtitle("Number of Information Links Accessed") ///
>         ytitle("Density") ylabel(0(.1).4) yscale(range(0 .4)) ///
>         name(totallinks_density, replace)

.         
. graph combine time_on_camp_min_density totallinks_density ///
>                 ,       rows(1) iscale(1.1) scale(1) xsize(8)  ///
>                         graphregion(margin(zero)) scheme(s1color)  

.                         
. drop x_values* density_values*

. 
.         
. 
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. *Is Assignment to Treatment Groups Predicted by Covariates?
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. 
. 
. logit polls_treatment polit_soph b1.voteprob_if_no_fine_AU age education female income if samp==1

Iteration 0:   log likelihood = -1170.8805  
Iteration 1:   log likelihood = -1168.9307  
Iteration 2:   log likelihood = -1168.9297  
Iteration 3:   log likelihood = -1168.9297  

Logistic regression                               Number of obs   =       1854
                                                  LR chi2(8)      =       3.90
                                                  Prob > chi2     =     0.8659
Log likelihood = -1168.9297                       Pseudo R2       =     0.0017

----------------------------------------------------------------------------------------------
             polls_treatment |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
                  polit_soph |   .0163444   .0710859     0.23   0.818    -.1229813    .1556701
                             |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.0631803   .1184548    -0.53   0.594    -.2953473    .1689868
Moderately Compelled Voters  |  -.2442991   .1704598    -1.43   0.152    -.5783941    .0897958
  Strongly Compelled Voters  |  -.1072606   .2534387    -0.42   0.672    -.6039913    .3894701
                             |
                         age |  -.0030093   .0035419    -0.85   0.396    -.0099512    .0039327
                   education |  -.0252828   .0276579    -0.91   0.361    -.0794913    .0289257
                      female |  -.0697095   .1020394    -0.68   0.495     -.269703    .1302839
                      income |      .0153   .0344108     0.44   0.657    -.0521439    .0827439
                       _cons |   1.012449   .2631894     3.85   0.000     .4966073    1.528291
----------------------------------------------------------------------------------------------

. 
. 
.         
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. *FIGURES 3 AND 4
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. ************************************************
. 
. 
. ********
. *Time Spent on Campaign
. ********
. reg time_on_camp_min b1.voteprob_if_no_fine_AU if samp == 1

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  3,  1913) =    4.52
       Model |   83.710073     3  27.9033577           Prob > F      =  0.0037
    Residual |  11819.0459  1913  6.17827806           R-squared     =  0.0070
-------------+------------------------------           Adj R-squared =  0.0055
       Total |   11902.756  1916  6.21229436           Root MSE      =  2.4856

----------------------------------------------------------------------------------------------
            time_on_camp_min |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2962958   .1290185    -2.30   0.022    -.5493274   -.0432641
Moderately Compelled Voters  |  -.4394517   .1879396    -2.34   0.019    -.8080398   -.0708636
  Strongly Compelled Voters  |  -.7544424   .2803329    -2.69   0.007    -1.304233   -.2046521
                             |
                       _cons |   1.730325   .0768175    22.53   0.000      1.57967     1.88098
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) atmeans post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      t    P>|t|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2962958   .1290185    -2.30   0.022    -.5086151   -.0839764
Moderately Compelled Voters  |  -.4394517   .1879396    -2.34   0.019    -.7487347   -.1301687
  Strongly Compelled Voters  |  -.7544424   .2803329    -2.69   0.007    -1.215772   -.2931123
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store time_on_camp_min_no_soph

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Minutes Spent Gathering Information" "Relative to Voluntary Voters"
> ) level(90) ///
>         recast(scatter) mcolor(black) msize(large) xlabel(-1.5(.5).5)   ///
>         ciopts(lpattern(solid) lcolor(black*.9)) xsize(11) scale(1.5) ///
>         name(time_on_camp_min_no_soph, replace) title("Without Control for Political Sophistication")

. 
. 
.         
. ********
. *Number of Links Accessed 
. ********
. *create exposure variable, as those in the treatment groups saw 21 links and those in the control saw 20
. gen exposure = .
(2220 missing values generated)

. replace exposure = 20 if polls_treatment == 0
(722 real changes made)

. replace exposure = 21 if polls_treatment == 1
(1498 real changes made)

. 
. nbreg totallinks b1.voteprob_if_no_fine_AU if samp == 1, exposure(exposure)

Fitting Poisson model:

Iteration 0:   log likelihood = -8824.8142  
Iteration 1:   log likelihood = -8824.8127  
Iteration 2:   log likelihood = -8824.8127  

Fitting constant-only model:

Iteration 0:   log likelihood = -4585.9298  
Iteration 1:   log likelihood = -4188.4241  
Iteration 2:   log likelihood = -4188.3928  
Iteration 3:   log likelihood = -4188.3928  

Fitting full model:

Iteration 0:   log likelihood = -4182.8925  
Iteration 1:   log likelihood = -4182.8422  
Iteration 2:   log likelihood = -4182.8422  

Negative binomial regression                      Number of obs   =       1917
                                                  LR chi2(3)      =      11.10
Dispersion     = mean                             Prob > chi2     =     0.0112
Log likelihood = -4182.8422                       Pseudo R2       =     0.0013

----------------------------------------------------------------------------------------------
                  totallinks |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1570146   .0956359    -1.64   0.101    -.3444575    .0304284
Moderately Compelled Voters  |  -.3142666   .1403446    -2.24   0.025    -.5893368   -.0391963
  Strongly Compelled Voters  |  -.5750443   .2125385    -2.71   0.007    -.9916122   -.1584764
                             |
                       _cons |  -1.669027   .0567021   -29.44   0.000    -1.780161   -1.557893
                ln(exposure) |          1  (exposure)
-----------------------------+----------------------------------------------------------------
                    /lnalpha |   1.134359    .042121                      1.051803    1.216915
-----------------------------+----------------------------------------------------------------
                       alpha |    3.10918   .1309618                      2.862809    3.376754
----------------------------------------------------------------------------------------------
Likelihood-ratio test of alpha=0:  chibar2(01) = 9283.94 Prob>=chibar2 = 0.000

. margins, dydx(voteprob_if_no_fine_AU) level(90) atmeans predict(n) post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OIM

Expression   : Predicted number of events, predict(n)
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.5660638   .3384421    -1.67   0.094    -1.122752   -.0093761
Moderately Compelled Voters  |  -1.050549    .426847    -2.46   0.014     -1.75265   -.3484486
  Strongly Compelled Voters  |  -1.703625   .5003878    -3.40   0.001     -2.52669   -.8805607
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store totallinks_no_soph

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Information Links Accessed" "Relative to Voluntary Voters") level(9
> 0)  ///
>         recast(scatter) mcolor(black) msize(large) xlabel(-4(1)1)   ///
>         ciopts(lpattern(solid) lcolor(black*.9)) xsize(11) scale(1.5) ///
>         name(totallinks_no_soph, replace)  title("Without Control for Political Sophistication")

.  
. drop exposure

. 
.                         
. 
. ********
. *Time Spent on Campaign, With Control for Political Sophistication
. ********
. reg time_on_camp_min b1.voteprob_if_no_fine_AU polit_soph if samp == 1

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  4,  1912) =    4.02
       Model |  99.2686312     4  24.8171578           Prob > F      =  0.0030
    Residual |  11803.4874  1912  6.17337205           R-squared     =  0.0083
-------------+------------------------------           Adj R-squared =  0.0063
       Total |   11902.756  1916  6.21229436           Root MSE      =  2.4846

----------------------------------------------------------------------------------------------
            time_on_camp_min |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2440006   .1331077    -1.83   0.067    -.5050522    .0170509
Moderately Compelled Voters  |  -.3343335   .1991925    -1.68   0.093    -.7249909    .0563239
  Strongly Compelled Voters  |  -.6207951   .2925942    -2.12   0.034    -1.194632   -.0469578
                             |
                  polit_soph |   .1200496   .0756201     1.59   0.113     -.028257    .2683562
                       _cons |   1.690518   .0807774    20.93   0.000     1.532097    1.848939
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) atmeans post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)
               polit_soph      =    .0556431 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      t    P>|t|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2440006   .1331077    -1.83   0.067    -.4630495   -.0249518
Moderately Compelled Voters  |  -.3343335   .1991925    -1.68   0.093    -.6621348   -.0065322
  Strongly Compelled Voters  |  -.6207951   .2925942    -2.12   0.034    -1.102303   -.1392872
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store time_on_camp_min_with_soph

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Minutes Spent Gathering Information" "Relative to Voluntary Voters"
> ) level(90) ///
>         recast(scatter) mcolor(gs7) msize(large) xlabel(-1.5(.5).5)    ///
>         ciopts(lpattern(solid) lcolor(gs7*.9)) xsize(11) scale(1.5) ///
>         name(time_on_camp_min_with_soph, replace)  title("With Control for Political Sophistication")

. 
. 
.         
. ********
. *Number of Links Accessed, With Control for Political Sophistication 
. ********
. *create exposure variable, as those in the treatment groups saw 21 links and those in the control saw 20
. gen exposure = .
(2220 missing values generated)

. replace exposure = 20 if polls_treatment == 0
(722 real changes made)

. replace exposure = 21 if polls_treatment == 1
(1498 real changes made)

. 
. 
. nbreg totallinks b1.voteprob_if_no_fine_AU polit_soph if samp == 1, exposure(exposure)

Fitting Poisson model:

Iteration 0:   log likelihood = -8741.4763  
Iteration 1:   log likelihood = -8741.4745  
Iteration 2:   log likelihood = -8741.4745  

Fitting constant-only model:

Iteration 0:   log likelihood = -4585.9298  
Iteration 1:   log likelihood = -4188.4241  
Iteration 2:   log likelihood = -4188.3928  
Iteration 3:   log likelihood = -4188.3928  

Fitting full model:

Iteration 0:   log likelihood = -4176.0637  
Iteration 1:   log likelihood = -4175.7984  
Iteration 2:   log likelihood = -4175.7982  

Negative binomial regression                      Number of obs   =       1917
                                                  LR chi2(4)      =      25.19
Dispersion     = mean                             Prob > chi2     =     0.0000
Log likelihood = -4175.7982                       Pseudo R2       =     0.0030

----------------------------------------------------------------------------------------------
                  totallinks |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.0540024   .0991159    -0.54   0.586    -.2482661    .1402612
Moderately Compelled Voters  |  -.1310618   .1482913    -0.88   0.377    -.4217073    .1595838
  Strongly Compelled Voters  |  -.3294235   .2217275    -1.49   0.137    -.7640014    .1051545
                             |
                  polit_soph |   .2123384   .0563214     3.77   0.000     .1019504    .3227264
                       _cons |  -1.755144   .0599879   -29.26   0.000    -1.872718    -1.63757
                ln(exposure) |          1  (exposure)
-----------------------------+----------------------------------------------------------------
                    /lnalpha |   1.122902   .0422554                      1.040083    1.205721
-----------------------------+----------------------------------------------------------------
                       alpha |   3.073761   .1298831                      2.829451    3.339166
----------------------------------------------------------------------------------------------
Likelihood-ratio test of alpha=0:  chibar2(01) = 9131.35 Prob>=chibar2 = 0.000

. margins, dydx(voteprob_if_no_fine_AU) level(90) atmeans predict(n) post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OIM

Expression   : Predicted number of events, predict(n)
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)
               polit_soph      =    .0556431 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1901277   .3467505    -0.55   0.583    -.7604816    .3802262
Moderately Compelled Voters  |  -.4442554   .4830857    -0.92   0.358    -1.238861    .3503499
  Strongly Compelled Voters  |  -1.015053    .599262    -1.69   0.090    -2.000751   -.0293548
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store totallinks_with_soph

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Information Links Accessed" "Relative to Voluntary Voters") level(9
> 0)  ///
>         recast(scatter) mcolor(gs7) msize(large) xlabel(-4(1)1)    ///
>         ciopts(lpattern(solid) lcolor(gs7*.9)) xsize(11) scale(1.5) ///
>         name(totallinks_with_soph, replace)  title("With Control for Political Sophistication")

.  
. drop exposure

. 
. 
. 
. ********
. *FIGURE 3: Time Spent on Campaign
. ********
. graph combine time_on_camp_min_no_soph time_on_camp_min_with_soph ///
>                 ,       rows(2) iscale(.65) scale(1) xsize(7) ///
>                         graphregion(margin(zero)) scheme(s1color)  xcommon      

. 
. ********
. *FIGURE 4: Number of Links Accessed
. ********
. graph combine totallinks_no_soph totallinks_with_soph ///
>                 ,       rows(2) iscale(.65) scale(1) xsize(7) ///
>                         graphregion(margin(zero)) scheme(s1color)  xcommon      

.                         
.                 
.                 
. 
. 
.                 
. ************************************************************************************************
. ************************************************************************************************
. ************************************************************************************************
. ************************************************************************************************
. ************************************************************************************************
. *SUPPLEMENTAL MATERIAL
. ************************************************************************************************
. ************************************************************************************************
. ************************************************************************************************
. ************************************************************************************************
. ************************************************************************************************
. 
.                 
.         
. ********
. *FIGURE A.1: Differences in Political Sophistication According to Voter Compulsion
. ********
. reg polit_soph b1.voteprob_if_no_fine_AU if samp == 1

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  3,  1913) =  135.56
       Model |  229.496601     3  76.4988669           Prob > F      =  0.0000
    Residual |  1079.56274  1913  .564329711           R-squared     =  0.1753
-------------+------------------------------           Adj R-squared =  0.1740
       Total |  1309.05934  1916  .683225124           Root MSE      =  .75122

----------------------------------------------------------------------------------------------
                  polit_soph |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.4356125   .0389928   -11.17   0.000    -.5120854   -.3591396
Moderately Compelled Voters  |  -.8756233   .0568004   -15.42   0.000    -.9870204   -.7642261
  Strongly Compelled Voters  |  -1.113268   .0847241   -13.14   0.000    -1.279429   -.9471063
                             |
                       _cons |   .3315877   .0232163    14.28   0.000     .2860558    .3771197
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) atmeans post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      t    P>|t|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.4356125   .0389928   -11.17   0.000    -.4997811    -.371444
Moderately Compelled Voters  |  -.8756233   .0568004   -15.42   0.000    -.9690968   -.7821497
  Strongly Compelled Voters  |  -1.113268   .0847241   -13.14   0.000    -1.252694   -.9738413
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Political Sophistication" "Relative to Voluntary Voters") level(90)      ///
>         recast(scatter) mcolor(black) msize(large)    ///
>         ciopts(lpattern(solid) lcolor(black*.9)) xsize(13) scale(1.5) 

.         
. ********
. *Figure A.2: Differences in Satisfaction with Democracy According to Voter Compulsion
. ********
. logit sat_dich b1.voteprob_if_no_fine_AU if samp == 1

Iteration 0:   log likelihood = -1216.5446  
Iteration 1:   log likelihood = -1191.1834  
Iteration 2:   log likelihood = -1191.0767  
Iteration 3:   log likelihood = -1191.0766  

Logistic regression                               Number of obs   =       1895
                                                  LR chi2(3)      =      50.94
                                                  Prob > chi2     =     0.0000
Log likelihood = -1191.0766                       Pseudo R2       =     0.0209

----------------------------------------------------------------------------------------------
                    sat_dich |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0711598    .113033     0.63   0.529    -.1503809    .2927004
Moderately Compelled Voters  |  -.5601584    .156101    -3.59   0.000    -.8661108    -.254206
  Strongly Compelled Voters  |  -1.407835   .2389864    -5.89   0.000     -1.87624   -.9394299
                             |
                       _cons |   .7677978    .066708    11.51   0.000     .6370526     .898543
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) predict(p) level(90) atmeans post

Conditional marginal effects                      Number of obs   =       1895
Model VCE    : OIM

Expression   : Pr(sat_dich), predict(p)
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5477573 (mean)
               2.voteprob~U    =    .3007916 (mean)
               3.voteprob~U    =     .107124 (mean)
               4.voteprob~U    =    .0443272 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0152013   .0240461     0.63   0.527    -.0243511    .0547536
Moderately Compelled Voters  |  -.1313202   .0377746    -3.48   0.001    -.1934538   -.0691866
  Strongly Compelled Voters  |  -.3378061   .0538482    -6.27   0.000    -.4263785   -.2492338
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Pr(Fairly or Very Satisfied with Democracy)" "Relative to Voluntary Voters") level(90)
>     ///
>         recast(scatter) mcolor(black) msize(large)    ///
>         ciopts(lpattern(solid) lcolor(black*.9)) xsize(13) scale(1.5) 

. 
. 
. ********
. *Figure A.3: Previous Vote Choice According to Voter Compulsion
. ********
. mlogit vote_choice_AU_prev_elec b1.voteprob_if_no_fine_AU if samp==1, base(3)

Iteration 0:   log likelihood = -2754.0662  
Iteration 1:   log likelihood = -2717.7971  
Iteration 2:   log likelihood = -2714.1918  
Iteration 3:   log likelihood = -2714.0418  
Iteration 4:   log likelihood = -2714.0114  
Iteration 5:   log likelihood = -2714.0049  
Iteration 6:   log likelihood = -2714.0034  
Iteration 7:   log likelihood =  -2714.003  
Iteration 8:   log likelihood =  -2714.003  
Iteration 9:   log likelihood = -2714.0029  

Multinomial logistic regression                   Number of obs   =       1900
                                                  LR chi2(15)     =      80.13
                                                  Prob > chi2     =     0.0000
Log likelihood = -2714.0029                       Pseudo R2       =     0.0145

----------------------------------------------------------------------------------------------
    vote_choice_AU_prev_elec |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
Green                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1892803   .1889118    -1.00   0.316    -.5595406      .18098
Moderately Compelled Voters  |  -.3576723   .3051132    -1.17   0.241    -.9556833    .2403386
  Strongly Compelled Voters  |  -.2035154   .5158464    -0.39   0.693    -1.214556     .807525
                             |
                       _cons |  -1.077387   .1027374   -10.49   0.000    -1.278748   -.8760254
-----------------------------+----------------------------------------------------------------
Labor                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0898329   .1237989     0.73   0.468    -.1528085    .3324743
Moderately Compelled Voters  |   .0230544   .1879075     0.12   0.902    -.3452376    .3913464
  Strongly Compelled Voters  |   .5535982    .300196     1.84   0.065    -.0347752    1.141972
                             |
                       _cons |   .0823076   .0717643     1.15   0.251    -.0583478     .222963
-----------------------------+----------------------------------------------------------------
Liberal                      |  (base outcome)
-----------------------------+----------------------------------------------------------------
National                     |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .1634659   .3730397     0.44   0.661    -.5676786    .8946103
Moderately Compelled Voters  |    .679874   .4571942     1.49   0.137      -.21621    1.575958
  Strongly Compelled Voters  |  -13.39907   806.6276    -0.02   0.987     -1594.36    1567.562
                             |
                       _cons |  -2.877057   .2242769   -12.83   0.000    -3.316631   -2.437482
-----------------------------+----------------------------------------------------------------
Other                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .3426066   .1984503     1.73   0.084    -.0463489    .7315622
Moderately Compelled Voters  |   .9643772   .2445054     3.94   0.000     .4851555    1.443599
  Strongly Compelled Voters  |   1.657495    .347694     4.77   0.000     .9760276    2.338963
                             |
                       _cons |   -1.55212    .123851   -12.53   0.000    -1.794863   -1.309376
-----------------------------+----------------------------------------------------------------
Abstained                    |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   1.251931   .2374129     5.27   0.000     .7866101    1.717252
Moderately Compelled Voters  |   1.172314   .3231273     3.63   0.000     .5389956    1.805631
  Strongly Compelled Voters  |   1.614134   .4620953     3.49   0.000     .7084439    2.519824
                             |
                       _cons |  -2.425047   .1816131   -13.35   0.000    -2.781002   -2.069092
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) predict(pr outcome(1)) atmeans post

Conditional marginal effects                      Number of obs   =       1900
Model VCE    : OIM

Expression   : Pr(vote_choice_AU_prev_elec==Green), predict(pr outcome(1))
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5463158 (mean)
               2.voteprob~U    =    .2994737 (mean)
               3.voteprob~U    =    .1094737 (mean)
               4.voteprob~U    =    .0447368 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |    -.03272   .0157116    -2.08   0.037    -.0585633   -.0068767
Moderately Compelled Voters  |  -.0502348   .0206194    -2.44   0.015    -.0841507   -.0163189
  Strongly Compelled Voters  |  -.0635241   .0274742    -2.31   0.021    -.1087152    -.018333
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store Green

. 
. mlogit vote_choice_AU_prev_elec b1.voteprob_if_no_fine_AU if samp==1, base(3)

Iteration 0:   log likelihood = -2754.0662  
Iteration 1:   log likelihood = -2717.7971  
Iteration 2:   log likelihood = -2714.1918  
Iteration 3:   log likelihood = -2714.0418  
Iteration 4:   log likelihood = -2714.0114  
Iteration 5:   log likelihood = -2714.0049  
Iteration 6:   log likelihood = -2714.0034  
Iteration 7:   log likelihood =  -2714.003  
Iteration 8:   log likelihood =  -2714.003  
Iteration 9:   log likelihood = -2714.0029  

Multinomial logistic regression                   Number of obs   =       1900
                                                  LR chi2(15)     =      80.13
                                                  Prob > chi2     =     0.0000
Log likelihood = -2714.0029                       Pseudo R2       =     0.0145

----------------------------------------------------------------------------------------------
    vote_choice_AU_prev_elec |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
Green                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1892803   .1889118    -1.00   0.316    -.5595406      .18098
Moderately Compelled Voters  |  -.3576723   .3051132    -1.17   0.241    -.9556833    .2403386
  Strongly Compelled Voters  |  -.2035154   .5158464    -0.39   0.693    -1.214556     .807525
                             |
                       _cons |  -1.077387   .1027374   -10.49   0.000    -1.278748   -.8760254
-----------------------------+----------------------------------------------------------------
Labor                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0898329   .1237989     0.73   0.468    -.1528085    .3324743
Moderately Compelled Voters  |   .0230544   .1879075     0.12   0.902    -.3452376    .3913464
  Strongly Compelled Voters  |   .5535982    .300196     1.84   0.065    -.0347752    1.141972
                             |
                       _cons |   .0823076   .0717643     1.15   0.251    -.0583478     .222963
-----------------------------+----------------------------------------------------------------
Liberal                      |  (base outcome)
-----------------------------+----------------------------------------------------------------
National                     |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .1634659   .3730397     0.44   0.661    -.5676786    .8946103
Moderately Compelled Voters  |    .679874   .4571942     1.49   0.137      -.21621    1.575958
  Strongly Compelled Voters  |  -13.39907   806.6276    -0.02   0.987     -1594.36    1567.562
                             |
                       _cons |  -2.877057   .2242769   -12.83   0.000    -3.316631   -2.437482
-----------------------------+----------------------------------------------------------------
Other                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .3426066   .1984503     1.73   0.084    -.0463489    .7315622
Moderately Compelled Voters  |   .9643772   .2445054     3.94   0.000     .4851555    1.443599
  Strongly Compelled Voters  |   1.657495    .347694     4.77   0.000     .9760276    2.338963
                             |
                       _cons |   -1.55212    .123851   -12.53   0.000    -1.794863   -1.309376
-----------------------------+----------------------------------------------------------------
Abstained                    |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   1.251931   .2374129     5.27   0.000     .7866101    1.717252
Moderately Compelled Voters  |   1.172314   .3231273     3.63   0.000     .5389956    1.805631
  Strongly Compelled Voters  |   1.614134   .4620953     3.49   0.000     .7084439    2.519824
                             |
                       _cons |  -2.425047   .1816131   -13.35   0.000    -2.781002   -2.069092
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) predict(pr outcome(2)) atmeans post

Conditional marginal effects                      Number of obs   =       1900
Model VCE    : OIM

Expression   : Pr(vote_choice_AU_prev_elec==Labor), predict(pr outcome(2))
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5463158 (mean)
               2.voteprob~U    =    .2994737 (mean)
               3.voteprob~U    =    .1094737 (mean)
               4.voteprob~U    =    .0447368 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.0123178   .0253451    -0.49   0.627    -.0540068    .0293712
Moderately Compelled Voters  |   -.053638   .0360927    -1.49   0.137    -.1130052    .0057292
  Strongly Compelled Voters  |   .0098049   .0552578     0.18   0.859     -.081086    .1006959
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store Labor

. 
. mlogit vote_choice_AU_prev_elec b1.voteprob_if_no_fine_AU if samp==1, base(3)

Iteration 0:   log likelihood = -2754.0662  
Iteration 1:   log likelihood = -2717.7971  
Iteration 2:   log likelihood = -2714.1918  
Iteration 3:   log likelihood = -2714.0418  
Iteration 4:   log likelihood = -2714.0114  
Iteration 5:   log likelihood = -2714.0049  
Iteration 6:   log likelihood = -2714.0034  
Iteration 7:   log likelihood =  -2714.003  
Iteration 8:   log likelihood =  -2714.003  
Iteration 9:   log likelihood = -2714.0029  

Multinomial logistic regression                   Number of obs   =       1900
                                                  LR chi2(15)     =      80.13
                                                  Prob > chi2     =     0.0000
Log likelihood = -2714.0029                       Pseudo R2       =     0.0145

----------------------------------------------------------------------------------------------
    vote_choice_AU_prev_elec |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
Green                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1892803   .1889118    -1.00   0.316    -.5595406      .18098
Moderately Compelled Voters  |  -.3576723   .3051132    -1.17   0.241    -.9556833    .2403386
  Strongly Compelled Voters  |  -.2035154   .5158464    -0.39   0.693    -1.214556     .807525
                             |
                       _cons |  -1.077387   .1027374   -10.49   0.000    -1.278748   -.8760254
-----------------------------+----------------------------------------------------------------
Labor                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0898329   .1237989     0.73   0.468    -.1528085    .3324743
Moderately Compelled Voters  |   .0230544   .1879075     0.12   0.902    -.3452376    .3913464
  Strongly Compelled Voters  |   .5535982    .300196     1.84   0.065    -.0347752    1.141972
                             |
                       _cons |   .0823076   .0717643     1.15   0.251    -.0583478     .222963
-----------------------------+----------------------------------------------------------------
Liberal                      |  (base outcome)
-----------------------------+----------------------------------------------------------------
National                     |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .1634659   .3730397     0.44   0.661    -.5676786    .8946103
Moderately Compelled Voters  |    .679874   .4571942     1.49   0.137      -.21621    1.575958
  Strongly Compelled Voters  |  -13.39907   806.6276    -0.02   0.987     -1594.36    1567.562
                             |
                       _cons |  -2.877057   .2242769   -12.83   0.000    -3.316631   -2.437482
-----------------------------+----------------------------------------------------------------
Other                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .3426066   .1984503     1.73   0.084    -.0463489    .7315622
Moderately Compelled Voters  |   .9643772   .2445054     3.94   0.000     .4851555    1.443599
  Strongly Compelled Voters  |   1.657495    .347694     4.77   0.000     .9760276    2.338963
                             |
                       _cons |   -1.55212    .123851   -12.53   0.000    -1.794863   -1.309376
-----------------------------+----------------------------------------------------------------
Abstained                    |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   1.251931   .2374129     5.27   0.000     .7866101    1.717252
Moderately Compelled Voters  |   1.172314   .3231273     3.63   0.000     .5389956    1.805631
  Strongly Compelled Voters  |   1.614134   .4620953     3.49   0.000     .7084439    2.519824
                             |
                       _cons |  -2.425047   .1816131   -13.35   0.000    -2.781002   -2.069092
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) predict(pr outcome(3)) atmeans post

Conditional marginal effects                      Number of obs   =       1900
Model VCE    : OIM

Expression   : Pr(vote_choice_AU_prev_elec==Liberal), predict(pr outcome(3))
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5463158 (mean)
               2.voteprob~U    =    .2994737 (mean)
               3.voteprob~U    =    .1094737 (mean)
               4.voteprob~U    =    .0447368 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.0412433   .0245562    -1.68   0.093    -.0816346    -.000852
Moderately Compelled Voters  |  -.0564638   .0351696    -1.61   0.108    -.1143127    .0013851
  Strongly Compelled Voters  |   -.147574   .0467526    -3.16   0.002    -.2244753   -.0706728
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store Liberal

. 
. mlogit vote_choice_AU_prev_elec b1.voteprob_if_no_fine_AU if samp==1, base(3)

Iteration 0:   log likelihood = -2754.0662  
Iteration 1:   log likelihood = -2717.7971  
Iteration 2:   log likelihood = -2714.1918  
Iteration 3:   log likelihood = -2714.0418  
Iteration 4:   log likelihood = -2714.0114  
Iteration 5:   log likelihood = -2714.0049  
Iteration 6:   log likelihood = -2714.0034  
Iteration 7:   log likelihood =  -2714.003  
Iteration 8:   log likelihood =  -2714.003  
Iteration 9:   log likelihood = -2714.0029  

Multinomial logistic regression                   Number of obs   =       1900
                                                  LR chi2(15)     =      80.13
                                                  Prob > chi2     =     0.0000
Log likelihood = -2714.0029                       Pseudo R2       =     0.0145

----------------------------------------------------------------------------------------------
    vote_choice_AU_prev_elec |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
Green                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1892803   .1889118    -1.00   0.316    -.5595406      .18098
Moderately Compelled Voters  |  -.3576723   .3051132    -1.17   0.241    -.9556833    .2403386
  Strongly Compelled Voters  |  -.2035154   .5158464    -0.39   0.693    -1.214556     .807525
                             |
                       _cons |  -1.077387   .1027374   -10.49   0.000    -1.278748   -.8760254
-----------------------------+----------------------------------------------------------------
Labor                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0898329   .1237989     0.73   0.468    -.1528085    .3324743
Moderately Compelled Voters  |   .0230544   .1879075     0.12   0.902    -.3452376    .3913464
  Strongly Compelled Voters  |   .5535982    .300196     1.84   0.065    -.0347752    1.141972
                             |
                       _cons |   .0823076   .0717643     1.15   0.251    -.0583478     .222963
-----------------------------+----------------------------------------------------------------
Liberal                      |  (base outcome)
-----------------------------+----------------------------------------------------------------
National                     |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .1634659   .3730397     0.44   0.661    -.5676786    .8946103
Moderately Compelled Voters  |    .679874   .4571942     1.49   0.137      -.21621    1.575958
  Strongly Compelled Voters  |  -13.39907   806.6276    -0.02   0.987     -1594.36    1567.562
                             |
                       _cons |  -2.877057   .2242769   -12.83   0.000    -3.316631   -2.437482
-----------------------------+----------------------------------------------------------------
Other                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .3426066   .1984503     1.73   0.084    -.0463489    .7315622
Moderately Compelled Voters  |   .9643772   .2445054     3.94   0.000     .4851555    1.443599
  Strongly Compelled Voters  |   1.657495    .347694     4.77   0.000     .9760276    2.338963
                             |
                       _cons |   -1.55212    .123851   -12.53   0.000    -1.794863   -1.309376
-----------------------------+----------------------------------------------------------------
Abstained                    |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   1.251931   .2374129     5.27   0.000     .7866101    1.717252
Moderately Compelled Voters  |   1.172314   .3231273     3.63   0.000     .5389956    1.805631
  Strongly Compelled Voters  |   1.614134   .4620953     3.49   0.000     .7084439    2.519824
                             |
                       _cons |  -2.425047   .1816131   -13.35   0.000    -2.781002   -2.069092
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) predict(pr outcome(4)) atmeans post

Conditional marginal effects                      Number of obs   =       1900
Model VCE    : OIM

Expression   : Pr(vote_choice_AU_prev_elec==National), predict(pr outcome(4))
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5463158 (mean)
               2.voteprob~U    =    .2994737 (mean)
               3.voteprob~U    =    .1094737 (mean)
               4.voteprob~U    =    .0447368 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0008584   .0074417     0.12   0.908    -.0113821    .0130989
Moderately Compelled Voters  |   .0134236   .0132459     1.01   0.311    -.0083639    .0352111
  Strongly Compelled Voters  |  -.0202311   .0043699    -4.63   0.000    -.0274191   -.0130432
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store National

. 
. mlogit vote_choice_AU_prev_elec b1.voteprob_if_no_fine_AU if samp==1, base(3)

Iteration 0:   log likelihood = -2754.0662  
Iteration 1:   log likelihood = -2717.7971  
Iteration 2:   log likelihood = -2714.1918  
Iteration 3:   log likelihood = -2714.0418  
Iteration 4:   log likelihood = -2714.0114  
Iteration 5:   log likelihood = -2714.0049  
Iteration 6:   log likelihood = -2714.0034  
Iteration 7:   log likelihood =  -2714.003  
Iteration 8:   log likelihood =  -2714.003  
Iteration 9:   log likelihood = -2714.0029  

Multinomial logistic regression                   Number of obs   =       1900
                                                  LR chi2(15)     =      80.13
                                                  Prob > chi2     =     0.0000
Log likelihood = -2714.0029                       Pseudo R2       =     0.0145

----------------------------------------------------------------------------------------------
    vote_choice_AU_prev_elec |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
Green                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1892803   .1889118    -1.00   0.316    -.5595406      .18098
Moderately Compelled Voters  |  -.3576723   .3051132    -1.17   0.241    -.9556833    .2403386
  Strongly Compelled Voters  |  -.2035154   .5158464    -0.39   0.693    -1.214556     .807525
                             |
                       _cons |  -1.077387   .1027374   -10.49   0.000    -1.278748   -.8760254
-----------------------------+----------------------------------------------------------------
Labor                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0898329   .1237989     0.73   0.468    -.1528085    .3324743
Moderately Compelled Voters  |   .0230544   .1879075     0.12   0.902    -.3452376    .3913464
  Strongly Compelled Voters  |   .5535982    .300196     1.84   0.065    -.0347752    1.141972
                             |
                       _cons |   .0823076   .0717643     1.15   0.251    -.0583478     .222963
-----------------------------+----------------------------------------------------------------
Liberal                      |  (base outcome)
-----------------------------+----------------------------------------------------------------
National                     |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .1634659   .3730397     0.44   0.661    -.5676786    .8946103
Moderately Compelled Voters  |    .679874   .4571942     1.49   0.137      -.21621    1.575958
  Strongly Compelled Voters  |  -13.39907   806.6276    -0.02   0.987     -1594.36    1567.562
                             |
                       _cons |  -2.877057   .2242769   -12.83   0.000    -3.316631   -2.437482
-----------------------------+----------------------------------------------------------------
Other                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .3426066   .1984503     1.73   0.084    -.0463489    .7315622
Moderately Compelled Voters  |   .9643772   .2445054     3.94   0.000     .4851555    1.443599
  Strongly Compelled Voters  |   1.657495    .347694     4.77   0.000     .9760276    2.338963
                             |
                       _cons |   -1.55212    .123851   -12.53   0.000    -1.794863   -1.309376
-----------------------------+----------------------------------------------------------------
Abstained                    |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   1.251931   .2374129     5.27   0.000     .7866101    1.717252
Moderately Compelled Voters  |   1.172314   .3231273     3.63   0.000     .5389956    1.805631
  Strongly Compelled Voters  |   1.614134   .4620953     3.49   0.000     .7084439    2.519824
                             |
                       _cons |  -2.425047   .1816131   -13.35   0.000    -2.781002   -2.069092
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) predict(pr outcome(5)) atmeans post

Conditional marginal effects                      Number of obs   =       1900
Model VCE    : OIM

Expression   : Pr(vote_choice_AU_prev_elec==Other), predict(pr outcome(5))
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5463158 (mean)
               2.voteprob~U    =    .2994737 (mean)
               3.voteprob~U    =    .1094737 (mean)
               4.voteprob~U    =    .0447368 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0187944   .0147886     1.27   0.204    -.0055306    .0431195
Moderately Compelled Voters  |   .0921658   .0272143     3.39   0.001     .0474022    .1369293
  Strongly Compelled Voters  |   .1591952   .0467427     3.41   0.001     .0823103    .2360801
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store Other

. 
. mlogit vote_choice_AU_prev_elec b1.voteprob_if_no_fine_AU if samp==1, base(3)

Iteration 0:   log likelihood = -2754.0662  
Iteration 1:   log likelihood = -2717.7971  
Iteration 2:   log likelihood = -2714.1918  
Iteration 3:   log likelihood = -2714.0418  
Iteration 4:   log likelihood = -2714.0114  
Iteration 5:   log likelihood = -2714.0049  
Iteration 6:   log likelihood = -2714.0034  
Iteration 7:   log likelihood =  -2714.003  
Iteration 8:   log likelihood =  -2714.003  
Iteration 9:   log likelihood = -2714.0029  

Multinomial logistic regression                   Number of obs   =       1900
                                                  LR chi2(15)     =      80.13
                                                  Prob > chi2     =     0.0000
Log likelihood = -2714.0029                       Pseudo R2       =     0.0145

----------------------------------------------------------------------------------------------
    vote_choice_AU_prev_elec |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
Green                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1892803   .1889118    -1.00   0.316    -.5595406      .18098
Moderately Compelled Voters  |  -.3576723   .3051132    -1.17   0.241    -.9556833    .2403386
  Strongly Compelled Voters  |  -.2035154   .5158464    -0.39   0.693    -1.214556     .807525
                             |
                       _cons |  -1.077387   .1027374   -10.49   0.000    -1.278748   -.8760254
-----------------------------+----------------------------------------------------------------
Labor                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0898329   .1237989     0.73   0.468    -.1528085    .3324743
Moderately Compelled Voters  |   .0230544   .1879075     0.12   0.902    -.3452376    .3913464
  Strongly Compelled Voters  |   .5535982    .300196     1.84   0.065    -.0347752    1.141972
                             |
                       _cons |   .0823076   .0717643     1.15   0.251    -.0583478     .222963
-----------------------------+----------------------------------------------------------------
Liberal                      |  (base outcome)
-----------------------------+----------------------------------------------------------------
National                     |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .1634659   .3730397     0.44   0.661    -.5676786    .8946103
Moderately Compelled Voters  |    .679874   .4571942     1.49   0.137      -.21621    1.575958
  Strongly Compelled Voters  |  -13.39907   806.6276    -0.02   0.987     -1594.36    1567.562
                             |
                       _cons |  -2.877057   .2242769   -12.83   0.000    -3.316631   -2.437482
-----------------------------+----------------------------------------------------------------
Other                        |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .3426066   .1984503     1.73   0.084    -.0463489    .7315622
Moderately Compelled Voters  |   .9643772   .2445054     3.94   0.000     .4851555    1.443599
  Strongly Compelled Voters  |   1.657495    .347694     4.77   0.000     .9760276    2.338963
                             |
                       _cons |   -1.55212    .123851   -12.53   0.000    -1.794863   -1.309376
-----------------------------+----------------------------------------------------------------
Abstained                    |
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   1.251931   .2374129     5.27   0.000     .7866101    1.717252
Moderately Compelled Voters  |   1.172314   .3231273     3.63   0.000     .5389956    1.805631
  Strongly Compelled Voters  |   1.614134   .4620953     3.49   0.000     .7084439    2.519824
                             |
                       _cons |  -2.425047   .1816131   -13.35   0.000    -2.781002   -2.069092
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) predict(pr outcome(98)) atmeans post

Conditional marginal effects                      Number of obs   =       1900
Model VCE    : OIM

Expression   : Pr(vote_choice_AU_prev_elec==Abstained), predict(pr outcome(98))
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5463158 (mean)
               2.voteprob~U    =    .2994737 (mean)
               3.voteprob~U    =    .1094737 (mean)
               4.voteprob~U    =    .0447368 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   .0666282   .0136236     4.89   0.000     .0442194    .0890371
Moderately Compelled Voters  |   .0547472   .0202412     2.70   0.007     .0214534     .088041
  Strongly Compelled Voters  |   .0623291    .032137     1.94   0.052     .0094685    .1151897
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store Abstained

. 
.         
. coefplot ///
>         (Green, mcolor(green) ciopts(lcolor(green*.9))) ///
>         ,       scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>                 grid(glcolor(gray*.2) glpattern(dash)) ///
>                 xtitle("Difference in Pr(Voted for Green Party)" "Relative to Voluntary Voters") level(90)      ///
>                 recast(scatter) mcolor(black) msize(medium) title("Green Party")  xsize(11) scale(1.5)  ///
>                 name(Green, replace)

.                         
. coefplot ///
>         (Labor, mcolor(red) ciopts(lcolor(red*.9))) ///
>         ,       scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>                 grid(glcolor(gray*.2) glpattern(dash)) ///
>                 xtitle("Difference in Pr(Voted for Labor Party)" "Relative to Voluntary Voters") level(90)      ///
>                 recast(scatter) mcolor(black) msize(medium)    title("Labor Party")   xsize(11) scale(1.5) ///
>                 name(Labor, replace)

.                         
. coefplot ///
>         (Liberal, mcolor(blue) ciopts(lcolor(blue*.9))) ///
>         ,       scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>                 grid(glcolor(gray*.2) glpattern(dash)) ///
>                 xtitle("Difference in Pr(Voted for Liberal Party)" "Relative to Voluntary Voters") level(90)    ///
>                 recast(scatter) mcolor(black) msize(medium)   title("Liberal Party")  xsize(11) scale(1.5)  ///
>                 name(Liberal, replace)

.                         
. coefplot ///
>         (National, mcolor(yellow*1.5) ciopts(lcolor(yellow*1.35))) ///
>         ,       scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>                 grid(glcolor(gray*.2) glpattern(dash)) ///
>                 xtitle("Difference in Pr(Voted for National Party)" "Relative to Voluntary Voters") level(90)   ///
>                 recast(scatter) mcolor(black) msize(medium)    title("National Party")  xsize(11) scale(1.5)  ///
>                 name(National, replace)

.                 
. coefplot ///
>         (Other, mcolor(black) ciopts(lcolor(black*.9))) ///
>         ,       scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>                 grid(glcolor(gray*.2) glpattern(dash)) ///
>                 xtitle("Difference in Pr(Voted for Others)" "Relative to Voluntary Voters") level(90)   ///
>                 recast(scatter) mcolor(black) msize(medium)   title("Others")  xsize(11) scale(1.5)  ///
>                 name(Other, replace)

.                 
. coefplot ///
>         (Abstained, mcolor(pink) ciopts(lcolor(pink*.9))) ///
>         ,       scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>                 grid(glcolor(gray*.2) glpattern(dash)) ///
>                 xtitle("Difference in Pr(Abstained)" "Relative to Voluntary Voters") level(90)  ///
>                 recast(scatter) mcolor(black) msize(medium)   title("Abstained")  xsize(11) scale(1.5)  ///
>                 name(Abstained, replace)

. 
. 
. graph combine Green Labor Liberal National Other Abstained ///
>                 ,       rows(3) iscale(.55) scale(1)    xsize(10) ///
>                         graphregion(margin(zero)) scheme(s1color)  xcommon      

. 
. 
. 
. ********
. *FIGURE B.1: Time Spent on Campaign, IPW
. ********                        
. teffects ipw (time_on_camp_min) (voteprob_if_no_fine_AU age education female income polit_soph i.satdemoc i.vote_cho
> ice_AU_prev_elec, mlogit) if samp == 1, aequations atet level(90)

Iteration 0:   EE criterion =  2.733e-11  
Iteration 1:   EE criterion =  9.644e-18  

Treatment-effects estimation                    Number of obs      =      1818
Estimator      : inverse-probability weights
Outcome model  : weighted mean
Treatment model: (multinomial) logit
--------------------------------------------------------------------------------------------------------------------
                                                   |               Robust
                                  time_on_camp_min |      Coef.   Std. Err.      z    P>|z|     [90% Conf. Interval]
---------------------------------------------------+----------------------------------------------------------------
ATET                                               |
                            voteprob_if_no_fine_AU |
  (Slightly Compelled Voters vs Voluntary Voters)  |  -.3085918   .1763821    -1.75   0.080    -.5987146    -.018469
(Moderately Compelled Voters vs Voluntary Voters)  |  -.4686227   .2062396    -2.27   0.023    -.8078566   -.1293887
  (Strongly Compelled Voters vs Voluntary Voters)  |  -.8602765   .2017857    -4.26   0.000    -1.192184   -.5283686
---------------------------------------------------+----------------------------------------------------------------
POmean                                             |
                            voteprob_if_no_fine_AU |
                                 Voluntary Voters  |   1.750783    .148048    11.83   0.000     1.507266      1.9943
---------------------------------------------------+----------------------------------------------------------------
TME2                                               |
                                               age |  -.0230888   .0041354    -5.58   0.000     -.029891   -.0162866
                                         education |    .016066   .0321595     0.50   0.617    -.0368317    .0689637
                                            female |  -.1452873    .116349    -1.25   0.212    -.3366644    .0460898
                                            income |  -.0551691    .040103    -1.38   0.169    -.1211328    .0107945
                                        polit_soph |  -.6145761   .0794774    -7.73   0.000    -.7453048   -.4838475
                                                   |
                                          satdemoc |
                                                2  |    .571676   .1880225     3.04   0.002     .2624066    .8809454
                                                3  |   .4966005   .2090112     2.38   0.018     .1528076    .8403934
                                                4  |   .3543909   .2961101     1.20   0.231    -.1326668    .8414486
                                                   |
                          vote_choice_AU_prev_elec |
                                            Labor  |    .192621   .2033769     0.95   0.344    -.1419043    .5271463
                                          Liberal  |   .2901927   .2093636     1.39   0.166    -.0541798    .6345653
                                         National  |   .2360039   .4170651     0.57   0.571    -.4500072    .9220149
                                            Other  |    .374203   .2678118     1.40   0.162    -.0663083    .8147142
                                        Abstained  |   .7721553   .3177436     2.43   0.015     .2495136    1.294797
                                                   |
                                             _cons |   -.025267   .3938111    -0.06   0.949    -.6730286    .6224945
---------------------------------------------------+----------------------------------------------------------------
TME3                                               |
                                               age |  -.0258982   .0061787    -4.19   0.000    -.0360612   -.0157352
                                         education |  -.0652564   .0449772    -1.45   0.147    -.1392373    .0087245
                                            female |  -.4076987   .1756342    -2.32   0.020    -.6965913   -.1188061
                                            income |   -.007127   .0577651    -0.12   0.902    -.1021421    .0878881
                                        polit_soph |  -1.287055   .1239116   -10.39   0.000    -1.490872   -1.083239
                                                   |
                                          satdemoc |
                                                2  |   .7670317   .3436385     2.23   0.026     .2017966    1.332267
                                                3  |   1.244846   .3592756     3.46   0.001     .6538906    1.835802
                                                4  |   1.150948   .4547702     2.53   0.011     .4029171    1.898978
                                                   |
                          vote_choice_AU_prev_elec |
                                            Labor  |   .1812861   .3307357     0.55   0.584    -.3627257    .7252979
                                          Liberal  |   .4767311   .3408683     1.40   0.162    -.0839474     1.03741
                                         National  |   .8065215   .5073259     1.59   0.112    -.0279553    1.640998
                                            Other  |   .8686185   .3860293     2.25   0.024     .2336568     1.50358
                                        Abstained  |   .6170462   .4511055     1.37   0.171    -.1249563    1.359049
                                                   |
                                             _cons |  -1.305785   .5635094    -2.32   0.020    -2.232676   -.3788946
---------------------------------------------------+----------------------------------------------------------------
TME4                                               |
                                               age |  -.0345413   .0099699    -3.46   0.001    -.0509403   -.0181422
                                         education |  -.1709049   .0685649    -2.49   0.013    -.2836841   -.0581257
                                            female |  -.5772839   .2611725    -2.21   0.027    -1.006874   -.1476933
                                            income |    .008878   .0834878     0.11   0.915    -.1284472    .1462031
                                        polit_soph |  -1.589961   .2005577    -7.93   0.000    -1.919849   -1.260073
                                                   |
                                          satdemoc |
                                                2  |   1.597336   .9757084     1.64   0.102    -.0075612    3.202234
                                                3  |   2.468661   .9786102     2.52   0.012     .8589909    4.078332
                                                4  |   3.526369    .999269     3.53   0.000     1.882717     5.17002
                                                   |
                          vote_choice_AU_prev_elec |
                                            Labor  |    .590174   .5240342     1.13   0.260    -.2717856    1.452134
                                          Liberal  |   .4488288    .567015     0.79   0.429    -.4838279    1.381485
                                         National  |  -13.88084   .5779934   -24.02   0.000    -14.83155   -12.93012
                                            Other  |   1.256773   .5777348     2.18   0.030     .3064838    2.207062
                                        Abstained  |   .7902209   .6935288     1.14   0.255    -.3505325    1.930974
                                                   |
                                             _cons |   -3.01867   1.260625    -2.39   0.017    -5.092213   -.9451266
--------------------------------------------------------------------------------------------------------------------

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("ATET on Number of Minutes Spent Gathering Information" "Relative to Voluntary Voters") level(90)    
>     ///
>         recast(scatter) mcolor(red) msize(large) xlabel(-1.5(.5).5)    ///
>         ciopts(lpattern(solid) lcolor(red*.5)) xsize(11) scale(1.5) ///
>         coeflabels(  ///
>         r2vs1.voteprob_if_no_fine_AU = "Slightly Compelled Voters"  ///
>         r3vs1.voteprob_if_no_fine_AU = "Moderately Compelled Voters"  ///
>         r4vs1.voteprob_if_no_fine_AU = "Strongly Compelled Voters"  ///
>         ) 

. 
. ********
. *FIGURE B.2: Number of Links Accessed, IPW
. ********
. *ipwra used to execute ipw, as it allows for the Poisson link and a control for the election simulation to which one
>  was subject (to proxy exposure) 
. teffects ipwra (totallinks i.electionnum, poisson) (voteprob_if_no_fine_AU age education female income polit_soph i.
> satdemoc i.vote_choice_AU_prev_elec, mlogit) if samp == 1, aequations atet level(90)

Iteration 0:   EE criterion =  2.733e-11  
Iteration 1:   EE criterion =  1.012e-17  

Treatment-effects estimation                    Number of obs      =      1818
Estimator      : IPW regression adjustment
Outcome model  : Poisson
Treatment model: (multinomial) logit
--------------------------------------------------------------------------------------------------------------------
                                                   |               Robust
                                        totallinks |      Coef.   Std. Err.      z    P>|z|     [90% Conf. Interval]
---------------------------------------------------+----------------------------------------------------------------
ATET                                               |
                            voteprob_if_no_fine_AU |
  (Slightly Compelled Voters vs Voluntary Voters)  |  -.2959292   .3615871    -0.82   0.413    -.8906871    .2988287
(Moderately Compelled Voters vs Voluntary Voters)  |  -.6656843   .5451843    -1.22   0.222    -1.562433    .2310641
  (Strongly Compelled Voters vs Voluntary Voters)  |   -2.18086   .4485162    -4.86   0.000    -2.918604   -1.443117
---------------------------------------------------+----------------------------------------------------------------
POmean                                             |
                            voteprob_if_no_fine_AU |
                                 Voluntary Voters  |   3.720003   .2715128    13.70   0.000     3.273404    4.166602
---------------------------------------------------+----------------------------------------------------------------
OME1                                               |
                                       electionnum |
                                                2  |  -.0766807   .1758904    -0.44   0.663    -.3659946    .2126333
                                                3  |  -.1246813   .1877187    -0.66   0.507    -.4334512    .1840885
                                                   |
                                             _cons |    1.38093   .1389971     9.93   0.000       1.1523     1.60956
---------------------------------------------------+----------------------------------------------------------------
OME2                                               |
                                       electionnum |
                                                2  |  -.0993757     .17065    -0.58   0.560    -.3800699    .1813186
                                                3  |  -.2839922   .1796377    -1.58   0.114    -.5794699    .0114855
                                                   |
                                             _cons |   1.356356   .1216191    11.15   0.000     1.156311    1.556402
---------------------------------------------------+----------------------------------------------------------------
OME3                                               |
                                       electionnum |
                                                2  |   .1236156   .3206036     0.39   0.700    -.4037303    .6509615
                                                3  |   .4968209   .3486272     1.43   0.154    -.0766197    1.070262
                                                   |
                                             _cons |    .876621    .208019     4.21   0.000     .5344602    1.218782
---------------------------------------------------+----------------------------------------------------------------
OME4                                               |
                                       electionnum |
                                                2  |  -.7732011   .6144312    -1.26   0.208     -1.78385    .2374483
                                                3  |  -.0680713   .5729689    -0.12   0.905    -1.010521    .8743788
                                                   |
                                             _cons |   .6444682   .4831087     1.33   0.182    -.1501748    1.439111
---------------------------------------------------+----------------------------------------------------------------
TME2                                               |
                                               age |  -.0230888   .0041354    -5.58   0.000     -.029891   -.0162866
                                         education |    .016066   .0321595     0.50   0.617    -.0368317    .0689637
                                            female |  -.1452873    .116349    -1.25   0.212    -.3366644    .0460898
                                            income |  -.0551691    .040103    -1.38   0.169    -.1211328    .0107945
                                        polit_soph |  -.6145761   .0794774    -7.73   0.000    -.7453048   -.4838475
                                                   |
                                          satdemoc |
                                                2  |    .571676   .1880225     3.04   0.002     .2624066    .8809454
                                                3  |   .4966005   .2090112     2.38   0.018     .1528076    .8403934
                                                4  |   .3543909   .2961101     1.20   0.231    -.1326668    .8414486
                                                   |
                          vote_choice_AU_prev_elec |
                                            Labor  |    .192621   .2033769     0.95   0.344    -.1419043    .5271463
                                          Liberal  |   .2901927   .2093636     1.39   0.166    -.0541798    .6345653
                                         National  |   .2360039   .4170651     0.57   0.571    -.4500072    .9220149
                                            Other  |    .374203   .2678118     1.40   0.162    -.0663083    .8147142
                                        Abstained  |   .7721553   .3177436     2.43   0.015     .2495136    1.294797
                                                   |
                                             _cons |   -.025267   .3938111    -0.06   0.949    -.6730286    .6224945
---------------------------------------------------+----------------------------------------------------------------
TME3                                               |
                                               age |  -.0258982   .0061787    -4.19   0.000    -.0360612   -.0157352
                                         education |  -.0652564   .0449772    -1.45   0.147    -.1392373    .0087245
                                            female |  -.4076987   .1756342    -2.32   0.020    -.6965913   -.1188061
                                            income |   -.007127   .0577651    -0.12   0.902    -.1021421    .0878881
                                        polit_soph |  -1.287055   .1239116   -10.39   0.000    -1.490872   -1.083239
                                                   |
                                          satdemoc |
                                                2  |   .7670317   .3436385     2.23   0.026     .2017966    1.332267
                                                3  |   1.244846   .3592756     3.46   0.001     .6538906    1.835802
                                                4  |   1.150948   .4547702     2.53   0.011     .4029171    1.898978
                                                   |
                          vote_choice_AU_prev_elec |
                                            Labor  |   .1812861   .3307357     0.55   0.584    -.3627257    .7252979
                                          Liberal  |   .4767311   .3408683     1.40   0.162    -.0839474     1.03741
                                         National  |   .8065215   .5073259     1.59   0.112    -.0279553    1.640998
                                            Other  |   .8686185   .3860293     2.25   0.024     .2336568     1.50358
                                        Abstained  |   .6170462   .4511055     1.37   0.171    -.1249563    1.359049
                                                   |
                                             _cons |  -1.305785   .5635094    -2.32   0.020    -2.232676   -.3788946
---------------------------------------------------+----------------------------------------------------------------
TME4                                               |
                                               age |  -.0345413   .0099699    -3.46   0.001    -.0509403   -.0181422
                                         education |  -.1709049   .0685649    -2.49   0.013    -.2836841   -.0581257
                                            female |  -.5772839   .2611725    -2.21   0.027    -1.006874   -.1476933
                                            income |    .008878   .0834878     0.11   0.915    -.1284472    .1462031
                                        polit_soph |  -1.589961   .2005577    -7.93   0.000    -1.919849   -1.260073
                                                   |
                                          satdemoc |
                                                2  |   1.597336   .9757084     1.64   0.102    -.0075612    3.202234
                                                3  |   2.468661   .9786102     2.52   0.012     .8589909    4.078332
                                                4  |   3.526369    .999269     3.53   0.000     1.882717     5.17002
                                                   |
                          vote_choice_AU_prev_elec |
                                            Labor  |    .590174   .5240342     1.13   0.260    -.2717856    1.452134
                                          Liberal  |   .4488288    .567015     0.79   0.429    -.4838279    1.381485
                                         National  |  -13.88084   .5779934   -24.02   0.000    -14.83155   -12.93012
                                            Other  |   1.256773   .5777348     2.18   0.030     .3064838    2.207062
                                        Abstained  |   .7902209   .6935288     1.14   0.255    -.3505325    1.930974
                                                   |
                                             _cons |   -3.01867   1.260625    -2.39   0.017    -5.092213   -.9451266
--------------------------------------------------------------------------------------------------------------------

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("ATET on Number of Information Links Accessed" "Relative to Voluntary Voters") level(90) ///
>         recast(scatter) mcolor(red) msize(large) xlabel(-4(1)1)    ///
>         ciopts(lpattern(solid) lcolor(red*.5)) xsize(11) scale(1.5) ///
>         coeflabels(  ///
>         r2vs1.voteprob_if_no_fine_AU = "Slightly Compelled Voters"  ///
>         r3vs1.voteprob_if_no_fine_AU = "Moderately Compelled Voters"  ///
>         r4vs1.voteprob_if_no_fine_AU = "Strongly Compelled Voters"  ///
>         )       

.         
. 
. 
. ************************************************
. *FIGURES C.2 AND C.3
. ************************************************
. 
. 
. gen C = "C" //*Generate variables that serve as marker labels

. gen T = "T"

. 
. ********
. *FIGURE C.2: Time Spent on Campaign
. ********
. reg time_on_camp_min b1.voteprob_if_no_fine_AU##i.polls_treatment  if samp == 1 

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  7,  1909) =    1.96
       Model |  84.8868088     7   12.126687           Prob > F      =  0.0572
    Residual |  11817.8692  1909  6.19060722           R-squared     =  0.0071
-------------+------------------------------           Adj R-squared =  0.0035
       Total |   11902.756  1916  6.21229436           Root MSE      =  2.4881

---------------------------------------------------------------------------------------------------------------------
                                   time_on_camp_min |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------------------------------------+----------------------------------------------------------------
                             voteprob_if_no_fine_AU |
                         Slightly Compelled Voters  |  -.2758372    .226842    -1.22   0.224    -.7207214    .1690469
                       Moderately Compelled Voters  |  -.4775447   .3148019    -1.52   0.129    -1.094937    .1398471
                         Strongly Compelled Voters  |   -.660824   .4896896    -1.35   0.177    -1.621207    .2995588
                                                    |
                                    polls_treatment |
                            Treatment Group: Polls  |   .0433128   .1653748     0.26   0.793    -.2810216    .3676471
                                                    |
             voteprob_if_no_fine_AU#polls_treatment |
  Slightly Compelled Voters#Treatment Group: Polls  |  -.0296658    .275937    -0.11   0.914    -.5708355    .5115039
Moderately Compelled Voters#Treatment Group: Polls  |   .0636023   .3928005     0.16   0.871    -.7067611    .8339656
  Strongly Compelled Voters#Treatment Group: Polls  |  -.1387493   .5975359    -0.23   0.816    -1.310641    1.033143
                                                    |
                                              _cons |   1.700705    .136758    12.44   0.000     1.432494    1.968916
---------------------------------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) at(polls_treatment = (0)) atmeans post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)
               polls_treatment =           0

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      t    P>|t|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2758372    .226842    -1.22   0.224    -.6491402    .0974658
Moderately Compelled Voters  |  -.4775447   .3148019    -1.52   0.129    -.9955992    .0405097
  Strongly Compelled Voters  |   -.660824   .4896896    -1.35   0.177    -1.466683    .1450347
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store control

. reg time_on_camp_min b1.voteprob_if_no_fine_AU##i.polls_treatment  if samp == 1 

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  7,  1909) =    1.96
       Model |  84.8868088     7   12.126687           Prob > F      =  0.0572
    Residual |  11817.8692  1909  6.19060722           R-squared     =  0.0071
-------------+------------------------------           Adj R-squared =  0.0035
       Total |   11902.756  1916  6.21229436           Root MSE      =  2.4881

---------------------------------------------------------------------------------------------------------------------
                                   time_on_camp_min |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------------------------------------+----------------------------------------------------------------
                             voteprob_if_no_fine_AU |
                         Slightly Compelled Voters  |  -.2758372    .226842    -1.22   0.224    -.7207214    .1690469
                       Moderately Compelled Voters  |  -.4775447   .3148019    -1.52   0.129    -1.094937    .1398471
                         Strongly Compelled Voters  |   -.660824   .4896896    -1.35   0.177    -1.621207    .2995588
                                                    |
                                    polls_treatment |
                            Treatment Group: Polls  |   .0433128   .1653748     0.26   0.793    -.2810216    .3676471
                                                    |
             voteprob_if_no_fine_AU#polls_treatment |
  Slightly Compelled Voters#Treatment Group: Polls  |  -.0296658    .275937    -0.11   0.914    -.5708355    .5115039
Moderately Compelled Voters#Treatment Group: Polls  |   .0636023   .3928005     0.16   0.871    -.7067611    .8339656
  Strongly Compelled Voters#Treatment Group: Polls  |  -.1387493   .5975359    -0.23   0.816    -1.310641    1.033143
                                                    |
                                              _cons |   1.700705    .136758    12.44   0.000     1.432494    1.968916
---------------------------------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) at(polls_treatment = (1)) atmeans post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OLS

Expression   : Linear prediction, predict()
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)
               polls_treatment =           1

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      t    P>|t|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |   -.305503   .1571112    -1.94   0.052    -.5640535   -.0469525
Moderately Compelled Voters  |  -.4139425   .2349298    -1.76   0.078    -.8005553   -.0273297
  Strongly Compelled Voters  |  -.7995732   .3424226    -2.34   0.020    -1.363082   -.2360647
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store treatment

. coefplot        (control, mlabcolor(black) mlabel(C) mlabsize(tiny) mlabcolor(white) msymbol(circle) msize(vlarge)  
> mlabposition(0) mcolor(black) ciopts(lcolor(black*.9))) ///
>                         (treatment, mlabcolor(black) mlabel(T) mlabsize(tiny) msymbol(circle) msize(vlarge) mfcolor(
> white) mlabposition(0) mcolor(black) ciopts(lcolor(black*.9))) ///
>         , scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Minutes Spent Gathering Information" "Relative to Voluntary Voters"
> ) level(90) ///
>         recast(scatter)    ///
>         legend(order(2 "Control Group: No Polls" 4 "Treatment Group: Polls") rows(2) size(medsmall)) ///
>         ciopts(lpattern(solid) lcolor(black*.9)) xsize(11) scale(1.5) 

. 
.         
. ********
. *FIGURE C.3: Number of Links Accessed 
. ********
. *create exposure variable, as those in the treatment groups saw 21 links and those in the control saw 20
. gen exposure = .
(2220 missing values generated)

. replace exposure = 20 if polls_treatment == 0
(722 real changes made)

. replace exposure = 21 if polls_treatment == 1
(1498 real changes made)

. 
. 
. nbreg totallinks b1.voteprob_if_no_fine_AU##i.polls_treatment  if samp == 1 , exposure(exposure)

Fitting Poisson model:

Iteration 0:   log likelihood = -8803.9903  
Iteration 1:   log likelihood = -8803.9886  
Iteration 2:   log likelihood = -8803.9886  

Fitting constant-only model:

Iteration 0:   log likelihood = -4585.9298  
Iteration 1:   log likelihood = -4188.4241  
Iteration 2:   log likelihood = -4188.3928  
Iteration 3:   log likelihood = -4188.3928  

Fitting full model:

Iteration 0:   log likelihood = -4181.1611  
Iteration 1:   log likelihood = -4181.0752  
Iteration 2:   log likelihood = -4181.0752  

Negative binomial regression                      Number of obs   =       1917
                                                  LR chi2(7)      =      14.64
Dispersion     = mean                             Prob > chi2     =     0.0410
Log likelihood = -4181.0752                       Pseudo R2       =     0.0017

---------------------------------------------------------------------------------------------------------------------
                                         totallinks |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------------------------------------+----------------------------------------------------------------
                             voteprob_if_no_fine_AU |
                         Slightly Compelled Voters  |  -.1082613    .167106    -0.65   0.517     -.435783    .2192605
                       Moderately Compelled Voters  |  -.4861384   .2355031    -2.06   0.039     -.947716   -.0245608
                         Strongly Compelled Voters  |  -.5629974   .3687439    -1.53   0.127    -1.285722    .1597273
                                                    |
                                    polls_treatment |
                            Treatment Group: Polls  |  -.1400608   .1216388    -1.15   0.250    -.3784685     .098347
                                                    |
             voteprob_if_no_fine_AU#polls_treatment |
  Slightly Compelled Voters#Treatment Group: Polls  |  -.0800318   .2036755    -0.39   0.694    -.4792284    .3191649
Moderately Compelled Voters#Treatment Group: Polls  |   .2605737   .2931988     0.89   0.374    -.3140854    .8352327
  Strongly Compelled Voters#Treatment Group: Polls  |  -.0217391   .4509943    -0.05   0.962    -.9056718    .8621935
                                                    |
                                              _cons |  -1.575285   .1004805   -15.68   0.000    -1.772223   -1.378347
                                       ln(exposure) |          1  (exposure)
----------------------------------------------------+----------------------------------------------------------------
                                           /lnalpha |   1.131492   .0421545                       1.04887    1.214113
----------------------------------------------------+----------------------------------------------------------------
                                              alpha |   3.100278   .1306905                      2.854425    3.367306
---------------------------------------------------------------------------------------------------------------------
Likelihood-ratio test of alpha=0:  chibar2(01) = 9245.83 Prob>=chibar2 = 0.000

. margins, dydx(voteprob_if_no_fine_AU) level(90)  at(polls_treatment = (0)) atmeans predict(n) post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OIM

Expression   : Predicted number of events, predict(n)
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)
               polls_treatment =           0

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.4389984    .669048    -0.66   0.512    -1.539484    .6614877
Moderately Compelled Voters  |  -1.647217   .7063261    -2.33   0.020     -2.80902   -.4854143
  Strongly Compelled Voters  |  -1.841875   .9654666    -1.91   0.056    -3.429926   -.2538236
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store control

. nbreg totallinks b1.voteprob_if_no_fine_AU##i.polls_treatment  if samp == 1 , exposure(exposure)

Fitting Poisson model:

Iteration 0:   log likelihood = -8803.9903  
Iteration 1:   log likelihood = -8803.9886  
Iteration 2:   log likelihood = -8803.9886  

Fitting constant-only model:

Iteration 0:   log likelihood = -4585.9298  
Iteration 1:   log likelihood = -4188.4241  
Iteration 2:   log likelihood = -4188.3928  
Iteration 3:   log likelihood = -4188.3928  

Fitting full model:

Iteration 0:   log likelihood = -4181.1611  
Iteration 1:   log likelihood = -4181.0752  
Iteration 2:   log likelihood = -4181.0752  

Negative binomial regression                      Number of obs   =       1917
                                                  LR chi2(7)      =      14.64
Dispersion     = mean                             Prob > chi2     =     0.0410
Log likelihood = -4181.0752                       Pseudo R2       =     0.0017

---------------------------------------------------------------------------------------------------------------------
                                         totallinks |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------------------------------------+----------------------------------------------------------------
                             voteprob_if_no_fine_AU |
                         Slightly Compelled Voters  |  -.1082613    .167106    -0.65   0.517     -.435783    .2192605
                       Moderately Compelled Voters  |  -.4861384   .2355031    -2.06   0.039     -.947716   -.0245608
                         Strongly Compelled Voters  |  -.5629974   .3687439    -1.53   0.127    -1.285722    .1597273
                                                    |
                                    polls_treatment |
                            Treatment Group: Polls  |  -.1400608   .1216388    -1.15   0.250    -.3784685     .098347
                                                    |
             voteprob_if_no_fine_AU#polls_treatment |
  Slightly Compelled Voters#Treatment Group: Polls  |  -.0800318   .2036755    -0.39   0.694    -.4792284    .3191649
Moderately Compelled Voters#Treatment Group: Polls  |   .2605737   .2931988     0.89   0.374    -.3140854    .8352327
  Strongly Compelled Voters#Treatment Group: Polls  |  -.0217391   .4509943    -0.05   0.962    -.9056718    .8621935
                                                    |
                                              _cons |  -1.575285   .1004805   -15.68   0.000    -1.772223   -1.378347
                                       ln(exposure) |          1  (exposure)
----------------------------------------------------+----------------------------------------------------------------
                                           /lnalpha |   1.131492   .0421545                       1.04887    1.214113
----------------------------------------------------+----------------------------------------------------------------
                                              alpha |   3.100278   .1306905                      2.854425    3.367306
---------------------------------------------------------------------------------------------------------------------
Likelihood-ratio test of alpha=0:  chibar2(01) = 9245.83 Prob>=chibar2 = 0.000

. margins, dydx(voteprob_if_no_fine_AU) level(90)  at(polls_treatment = (1)) atmeans predict(n) post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : OIM

Expression   : Predicted number of events, predict(n)
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)
               polls_treatment =           1

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.6383327   .3861457    -1.65   0.098    -1.273486   -.0031796
Moderately Compelled Voters  |  -.7510512   .5406986    -1.39   0.165    -1.640421    .1383189
  Strongly Compelled Voters  |  -1.646701   .5783145    -2.85   0.004    -2.597944   -.6954584
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. estimates store treatment

. coefplot        (control, mlabcolor(black) mlabel(C) mlabsize(tiny) mlabcolor(white) msymbol(circle) msize(vlarge)  
> mlabposition(0) mcolor(black) ciopts(lcolor(black*.9))) ///
>                         (treatment, mlabcolor(black) mlabel(T) mlabsize(tiny) msymbol(circle) msize(vlarge) mfcolor(
> white) mlabposition(0) mcolor(black) ciopts(lcolor(black*.9))) ///
>         , scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Information Links Accessed" "Relative to Voluntary Voters") level(9
> 0)  ///
>         recast(scatter)   ///
>         legend(order(2 "Control Group: No Polls" 4 "Treatment Group: Polls") rows(2) size(medsmall)) ///
>         ciopts(lpattern(solid) lcolor(black*.9)) xsize(11) scale(1.5) 

.         
. 
. drop exposure

. 
. drop C T

. 
. 
. ********
. *Figure D.1: Time Spent Gathering Political Information and Voter Compulsion, Poisson Regression
. ********
. *Without Sophistication
. poisson time_on_camp_min b1.voteprob_if_no_fine_AU if samp == 1, robust
note: you are responsible for interpretation of noncount dep. variable

Iteration 0:   log pseudolikelihood =  -3971.937  
Iteration 1:   log pseudolikelihood = -3971.9364  
Iteration 2:   log pseudolikelihood = -3971.9364  

Poisson regression                                Number of obs   =       1917
                                                  Wald chi2(3)    =      19.07
                                                  Prob > chi2     =     0.0003
Log pseudolikelihood = -3971.9364                 Pseudo R2       =     0.0071

----------------------------------------------------------------------------------------------
                             |               Robust
            time_on_camp_min |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1878211   .0834339    -2.25   0.024    -.3513485   -.0242937
Moderately Compelled Voters  |  -.2929903   .1257705    -2.33   0.020    -.5394961   -.0464846
  Strongly Compelled Voters  |  -.5727223   .1537543    -3.72   0.000    -.8740753   -.2713694
                             |
                       _cons |   .5483091   .0478217    11.47   0.000     .4545804    .6420379
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) atmeans post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : Robust

Expression   : Predicted number of events, predict()
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2962958   .1282945    -2.31   0.021    -.5073215   -.0852701
Moderately Compelled Voters  |  -.4394517   .1714498    -2.56   0.010    -.7214615   -.1574419
  Strongly Compelled Voters  |  -.7544424   .1648726    -4.58   0.000    -1.025634   -.4832511
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Minutes Spent Gathering Information" "Relative to Voluntary Voters"
> ) level(90) ///
>         recast(scatter) mcolor(black) msize(large) xlabel(-1.5(.5).5)   ///
>         ciopts(lpattern(solid) lcolor(black*.9)) xsize(11) scale(1.5) ///
>         name(pois_time_on_camp_min_no_soph, replace) title("Without Control for Political Sophistication")

. 
. *With Sophistication
. poisson time_on_camp_min b1.voteprob_if_no_fine_AU polit_soph if samp == 1, robust
note: you are responsible for interpretation of noncount dep. variable

Iteration 0:   log pseudolikelihood = -3966.8969  
Iteration 1:   log pseudolikelihood = -3966.8964  
Iteration 2:   log pseudolikelihood = -3966.8964  

Poisson regression                                Number of obs   =       1917
                                                  Wald chi2(4)    =      22.58
                                                  Prob > chi2     =     0.0002
Log pseudolikelihood = -3966.8964                 Pseudo R2       =     0.0083

----------------------------------------------------------------------------------------------
                             |               Robust
            time_on_camp_min |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1538543   .0850157    -1.81   0.070    -.3204819    .0127733
Moderately Compelled Voters  |  -.2248923   .1311117    -1.72   0.086    -.4818665    .0320819
  Strongly Compelled Voters  |  -.4864995   .1643014    -2.96   0.003    -.8085243   -.1644747
                             |
                  polit_soph |   .0779539   .0468607     1.66   0.096    -.0138914    .1697992
                       _cons |    .520795   .0522656     9.96   0.000     .4183562    .6232337
----------------------------------------------------------------------------------------------

. margins, dydx(voteprob_if_no_fine_AU) level(90) atmeans post

Conditional marginal effects                      Number of obs   =       1917
Model VCE    : Robust

Expression   : Predicted number of events, predict()
dy/dx w.r.t. : 2.voteprob_if_no_fine_AU 3.voteprob_if_no_fine_AU 4.voteprob_if_no_fine_AU
at           : 1.voteprob~U    =    .5461659 (mean)
               2.voteprob~U    =    .2999478 (mean)
               3.voteprob~U    =    .1095462 (mean)
               4.voteprob~U    =    .0443401 (mean)
               polit_soph      =    .0556431 (mean)

----------------------------------------------------------------------------------------------
                             |            Delta-method
                             |      dy/dx   Std. Err.      z    P>|z|     [90% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2410965   .1310199    -1.84   0.066     -.456605    -.025588
Moderately Compelled Voters  |  -.3404998   .1855048    -1.84   0.066    -.6456281   -.0353715
  Strongly Compelled Voters  |  -.6512939    .186864    -3.49   0.000    -.9586579     -.34393
----------------------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. coefplot,  ///
>         scheme(s1color) xline(0, lpattern(dash) lcolor(black*.5)) ///
>         grid(glcolor(gray*.2) glpattern(dash)) ///
>         xtitle("Difference in Expected Number of Minutes Spent Gathering Information" "Relative to Voluntary Voters"
> ) level(90) ///
>         recast(scatter) mcolor(gs7) msize(large) xlabel(-1.5(.5).5)    ///
>         ciopts(lpattern(solid) lcolor(gs7*.9)) xsize(11) scale(1.5) ///
>         name(pois_time_on_camp_min_with_soph, replace)  title("With Control for Political Sophistication")

. 
. *Combine Graphs With and Without Control for Sophistication
. 
. graph combine pois_time_on_camp_min_no_soph pois_time_on_camp_min_with_soph ///
>                 ,       rows(2) iscale(.65) scale(1) xsize(7) ///
>                         graphregion(margin(zero)) scheme(s1color)  xcommon 

.                         
.                         
.                         
. ********                        
. *Table E.1: Time Spent Gathering Political Information and Voter Compulsion                     
. ********                        
. reg time_on_camp_min b1.voteprob_if_no_fine_AU if samp == 1 //*Model 1

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  3,  1913) =    4.52
       Model |   83.710073     3  27.9033577           Prob > F      =  0.0037
    Residual |  11819.0459  1913  6.17827806           R-squared     =  0.0070
-------------+------------------------------           Adj R-squared =  0.0055
       Total |   11902.756  1916  6.21229436           Root MSE      =  2.4856

----------------------------------------------------------------------------------------------
            time_on_camp_min |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2962958   .1290185    -2.30   0.022    -.5493274   -.0432641
Moderately Compelled Voters  |  -.4394517   .1879396    -2.34   0.019    -.8080398   -.0708636
  Strongly Compelled Voters  |  -.7544424   .2803329    -2.69   0.007    -1.304233   -.2046521
                             |
                       _cons |   1.730325   .0768175    22.53   0.000      1.57967     1.88098
----------------------------------------------------------------------------------------------

. reg time_on_camp_min b1.voteprob_if_no_fine_AU polit_soph if samp == 1  //*Model 2

      Source |       SS       df       MS              Number of obs =    1917
-------------+------------------------------           F(  4,  1912) =    4.02
       Model |  99.2686312     4  24.8171578           Prob > F      =  0.0030
    Residual |  11803.4874  1912  6.17337205           R-squared     =  0.0083
-------------+------------------------------           Adj R-squared =  0.0063
       Total |   11902.756  1916  6.21229436           Root MSE      =  2.4846

----------------------------------------------------------------------------------------------
            time_on_camp_min |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.2440006   .1331077    -1.83   0.067    -.5050522    .0170509
Moderately Compelled Voters  |  -.3343335   .1991925    -1.68   0.093    -.7249909    .0563239
  Strongly Compelled Voters  |  -.6207951   .2925942    -2.12   0.034    -1.194632   -.0469578
                             |
                  polit_soph |   .1200496   .0756201     1.59   0.113     -.028257    .2683562
                       _cons |   1.690518   .0807774    20.93   0.000     1.532097    1.848939
----------------------------------------------------------------------------------------------

.                         
.                         
. ********                        
. *Table E.2: The Amount of Political Information Gathered and Voter Compulsion
. ********        
. gen exposure = .
(2220 missing values generated)

. replace exposure = 20 if polls_treatment == 0
(722 real changes made)

. replace exposure = 21 if polls_treatment == 1
(1498 real changes made)

. 
. nbreg totallinks b1.voteprob_if_no_fine_AU if samp == 1, exposure(exposure) //*Model 1

Fitting Poisson model:

Iteration 0:   log likelihood = -8824.8142  
Iteration 1:   log likelihood = -8824.8127  
Iteration 2:   log likelihood = -8824.8127  

Fitting constant-only model:

Iteration 0:   log likelihood = -4585.9298  
Iteration 1:   log likelihood = -4188.4241  
Iteration 2:   log likelihood = -4188.3928  
Iteration 3:   log likelihood = -4188.3928  

Fitting full model:

Iteration 0:   log likelihood = -4182.8925  
Iteration 1:   log likelihood = -4182.8422  
Iteration 2:   log likelihood = -4182.8422  

Negative binomial regression                      Number of obs   =       1917
                                                  LR chi2(3)      =      11.10
Dispersion     = mean                             Prob > chi2     =     0.0112
Log likelihood = -4182.8422                       Pseudo R2       =     0.0013

----------------------------------------------------------------------------------------------
                  totallinks |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.1570146   .0956359    -1.64   0.101    -.3444575    .0304284
Moderately Compelled Voters  |  -.3142666   .1403446    -2.24   0.025    -.5893368   -.0391963
  Strongly Compelled Voters  |  -.5750443   .2125385    -2.71   0.007    -.9916122   -.1584764
                             |
                       _cons |  -1.669027   .0567021   -29.44   0.000    -1.780161   -1.557893
                ln(exposure) |          1  (exposure)
-----------------------------+----------------------------------------------------------------
                    /lnalpha |   1.134359    .042121                      1.051803    1.216915
-----------------------------+----------------------------------------------------------------
                       alpha |    3.10918   .1309618                      2.862809    3.376754
----------------------------------------------------------------------------------------------
Likelihood-ratio test of alpha=0:  chibar2(01) = 9283.94 Prob>=chibar2 = 0.000

. nbreg totallinks b1.voteprob_if_no_fine_AU polit_soph if samp == 1, exposure(exposure) //*Model 2

Fitting Poisson model:

Iteration 0:   log likelihood = -8741.4763  
Iteration 1:   log likelihood = -8741.4745  
Iteration 2:   log likelihood = -8741.4745  

Fitting constant-only model:

Iteration 0:   log likelihood = -4585.9298  
Iteration 1:   log likelihood = -4188.4241  
Iteration 2:   log likelihood = -4188.3928  
Iteration 3:   log likelihood = -4188.3928  

Fitting full model:

Iteration 0:   log likelihood = -4176.0637  
Iteration 1:   log likelihood = -4175.7984  
Iteration 2:   log likelihood = -4175.7982  

Negative binomial regression                      Number of obs   =       1917
                                                  LR chi2(4)      =      25.19
Dispersion     = mean                             Prob > chi2     =     0.0000
Log likelihood = -4175.7982                       Pseudo R2       =     0.0030

----------------------------------------------------------------------------------------------
                  totallinks |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
      voteprob_if_no_fine_AU |
  Slightly Compelled Voters  |  -.0540024   .0991159    -0.54   0.586    -.2482661    .1402612
Moderately Compelled Voters  |  -.1310618   .1482913    -0.88   0.377    -.4217073    .1595838
  Strongly Compelled Voters  |  -.3294235   .2217275    -1.49   0.137    -.7640014    .1051545
                             |
                  polit_soph |   .2123384   .0563214     3.77   0.000     .1019504    .3227264
                       _cons |  -1.755144   .0599879   -29.26   0.000    -1.872718    -1.63757
                ln(exposure) |          1  (exposure)
-----------------------------+----------------------------------------------------------------
                    /lnalpha |   1.122902   .0422554                      1.040083    1.205721
-----------------------------+----------------------------------------------------------------
                       alpha |   3.073761   .1298831                      2.829451    3.339166
----------------------------------------------------------------------------------------------
Likelihood-ratio test of alpha=0:  chibar2(01) = 9131.35 Prob>=chibar2 = 0.000

. 
. 
. drop exposure

. 
end of do-file

. log close
      name:  <unnamed>
       log:  /Users/singh/Google Drive/PLS/Research/Compulsory Voting/ERG CV/R&P submission materials/replication log,
>  R&P.log
  log type:  text
 closed on:  29 Aug 2017, 18:47:03
----------------------------------------------------------------------------------------------------------------------
